Significance: Accurate targeting, guidance and monitoring of interventional therapy in the brain are critical for maximizing their effectiveness and safety during and following neurosurgical procedures. Magnetic resonance imaging (MRI) is a critical tool for planning and guiding neurosurgical procedures. In most cases, the MRI is obtained during a pre-operative session; however, either brain shift, errors in device guidance, or device malfunction can lead to poor outcomes. In particular for infusion-based therapies, the location of the infusion cannula in the brain, the difficulty of predicting how agents will distribte through the complex nature of brain tumors, and loss of the therapeutic agent through backflow or other mechanisms may significantly influence the therapeutic outcome. The inseRT MRI system provides a unique solution for providing real-time, interactive brain imaging for drug infusion procedures by providing a workflow environment that is intuitive for neurosurgeons. Phase I Progress: A successful model for iteratively developing, testing, accessing, and revising our platform based on rapid customer feedback has been implemented during Phase I. The platform was used to successfully guide and monitor gene delivery into 12 survival NHP models in a protocol demanding more precision than human protocols. Specific Aims of Phase II: This project will further develop the inseRT MRI system as a commercial product for image-guided drug infusion procedures. In Specific Aim 1, the inseRT MRI platform interface will add the remaining features our collaborators in Neurosurgery are requesting for a simplified, methodical workflow that is similar to the stereotactic procedures used in operating rooms today. The technology will be evaluated by neurosurgeons to demonstrate localization of targeting within 0.75 mm in gel phantoms and cadaver heads. In Specific Aim 2, predictive models of drug infusion distribution, used only in surgical planning today, will be integrated into the inseRT MRI system. Real-time, quantitative drug tracer information from the infusion in progress will be used to improve the algorithm's ability to demonstrate the most likely final drug distribution to the surgeon. This information can be used by the surgeon to alter the infusion to meet the treatment goals during surgery. Quantitative infusion concentration results will be tested against non-real-time measurement techniques. In Specific Aim 3, the inseRT MRI system with improved interface and predictive drug distribution modeling will be evaluated in animal models. These studies are designed as inputs for upcoming FDA IDE and 510k submissions.